A rule-based scheduling method for ocean-going vessels

Abstract

The present invention discloses a rule-based ocean transport ship scheduling method, the method steps are as follows: establish an ocean transport ship scheduling model based on an existing ship schedule, initialize the set of cargoes that failed to be arranged DF, initialize the set of available ships; select the cargoes with the longest route distance in the set DP for scheme arrangement, judge whether the empty time and full load time of the cargoes are within the ship's available time window, update the cargo arrangement scheme to the ship's schedule table, judge whether the set to be arranged DP is empty, judge whether the set of failed arrangements DF is empty, and output the ship's schedule. The present invention is aimed at the ocean transport scenario of bulk industrial materials, constructs a multi-cargo fleet whole-ship transport scheduling optimization model, by setting ship screening and scheduling optimization rules, on the basis of ensuring the optimal overall available time of the fleet, based on the rule-based step-by-step iterative optimization and final arrangement of the generated cargo ship transport scheme, reducing the complexity of problem solving and improving the efficiency of algorithm optimization.

Description

Technical Field

[0001] The present invention particularly relates to a rule-based ocean transport vessel scheduling method. Background Art

[0002] Internationally, bulk industrial commodities (crude oil, refined oil products, natural gas, chemicals, etc.) are primarily transported by ship, typically by shippers operating their own fleets from fixed ports of origin to destination. These vessels are characterized by relatively fixed routes and ports, large cargo flows, and relatively stable flow directions. These vessels operate on short, but less stringent, schedules. Given the large volumes, high economic value, and high shipping costs of bulk industrial commodities, optimizing the allocation of vessel resources and increasing vessel availability is of great practical significance and practical value. Ship scheduling optimization is generally a nonlinear programming problem involving numerous constraints. Relying solely on manual experience for scheduling optimization lacks scientificity and precision, and is labor-intensive. Therefore, it is necessary to research models and methods for optimizing the allocation of vessel resources to address specific issues in shipping, thereby enabling automated ship scheduling optimization and supporting decision-making.

[0003] 1. Chinese patent "CN 106650980 B: A Genetic Algorithm-Based Ocean LNG Supply and Demand Scheduling Method" decomposes the ocean LNG supply and demand scheduling process into a single supply chromosome (x), which participates in evolutionary processes such as crossover and mutation, and a single demand chromosome (y), which does not. By rationally configuring fitness values, the priority of the three optimization requirements—time matching, mismatched time difference, and cargo volume matching—is controlled. This method guides the optimization of ocean LNG supply and demand scheduling solutions using a genetic algorithm, maximizing ocean LNG supply and demand matching.

[0004] Defects: This invention mainly targets application scenarios in which ships are matched with specified supply quantity and supply time, demand quantity and demand time, and the scheme scheduling is used to maximize the number of ships that meet the supply time and delivery time range, which is inconsistent with the application scenario of this invention. In addition, this invention does not take into account the existing ship schedule, as well as the route and sailing time when two adjacent voyages are connected.

[0005] 2. Chinese patent "CN103295061B A Ship Scheduling Method Based on Ant Colony Algorithm" proposes an improved adaptive ant colony algorithm. It adopts a new pheromone update strategy to adaptively and dynamically adjust the pheromone p and pheromone intensity Q on the paths passed by ants that fall into local convergence. This allows the algorithm to jump out of local convergence more quickly and prevent "premature maturity". At the same time, the pheromone values on all paths are limited to a range, which is beneficial to the algorithm's global search.

[0006] Defects: This invention is aimed at scheduling routes from a designated departure port to a destination port, which is inconsistent with the application scenario of the present invention and does not take into account the time limit requirements for cargo loading. Summary of the Invention

[0007] The purpose of this invention is to address existing problems and propose a rule-based ocean transport ship scheduling method for the ocean transport scenario of bulk industrial materials. Based on the established ship transport scheduling model and rules, it will iteratively optimize and generate ship transport plans for bulk industrial materials to improve decision-making efficiency and scientificity.

[0008] In order to achieve the above object, the technical solution adopted by the present invention is: a rule-based ocean transport ship scheduling method, the method steps are as follows:

[0009] Step 1: Establish an ocean shipping vessel scheduling model based on the existing shipping schedule;

[0010] Step 2: Given the set of goods to be arranged DP, initialize the set of goods that failed to be arranged DF;

[0011] Step 3: Initialize the set of available ships for cargo and described It consists of ships with non-empty transportation plans in the ship set S, It consists of ships with empty transport plans in the ship set S;

[0012] Step 4: Calculate the route distances in the set of goods to be arranged DP, and select the goods dp with the longest loading and unloading route distance in the set DP k Arrange plans;

[0013] Step 5: Set the ship's cargo capacity to be less than the cargo dp k Loading volume of the ship, from cargo dp k Available ship collection SG(dp k )

[0014] Step 6: dp the goods k Loading time window tg(dp k ) has cargo transportation plan, from cargo dp k Available ship collection SG(dp k )

[0015] Step 7: Determine the available ship set SG(dp k ) is empty, if SG(dp k ) is empty, indicating that the goods dp k No available ship, jump to step 11; if SG(dp k ) is not empty, jump to the next step;

[0016] Step 8: According to the goods dp k Loading time window tg(dp k ), loading and unloading routes, existing transportation plans for ships, and for all ships i ∈SG(dp k ), determine the cargo dp k Whether the empty time and full load time of the ship are within the available time window of the ship, for cargo dp k The ship of the transport time window is calculated as the arrangement scheme sch(s i ,dp k ) and the reduction in optimization time Δopt(s i ,dp k ), for no goods dp k The ship of the transportation time window is selected from the available ship set SG(dp k )

[0017] Step 9: Determine the available ship set SG(dp k ) is empty, if the available ship set SG(dp k ) is empty, indicating that the goods dp k Arrangement fails, jump to step 11; if the available ship set SG (dp k ) is not empty, jump to the next step;

[0018] Step 10, solve minΔopt(s i ,dp k ), s i ∈SG(dp k ) corresponding ships s k , as cargo dp k The optimal arrangement scheme sch o (s k ,dp k ), dp the goods k The arrangement scheme sch o (s k ,dp k ) Update to ships k Sailing Schedule dp the goods k Add to the arranged goods collection D, and at the same time transfer the goods dp k Delete from the set to be arranged DP, that is: DP = DP-dp k , and jump to step 12;

[0019] Step 11: dp the goods k Add it to the arrangement failure set DF, delete it from the set to be arranged DP, and jump to the next step;

[0020] Step 12: Determine whether the set to be arranged DP is empty. If the set to be arranged DP is not empty, jump to step 4 to arrange the next cargo. If the set to be arranged DP is empty, it means there is no cargo to be arranged, and jump to the next step.

[0021] Step 13: Determine whether the arrangement failure set DF is empty. If the arrangement failure set DF is empty, it means that all cargoes have been arranged successfully, and the updated ship schedule is output; if the arrangement failure set DF is not empty, it is necessary to determine the ship set with an empty schedule. Is it empty? If the collection If it is empty, it means that the goods in the set DF cannot be arranged in all available ships, which means that the arrangement of the goods in the set DF has failed, and the ship schedule of the successfully arranged goods is output.

[0022] Preferably, in step 1, the objective function of the ocean shipping ship scheduling model based on the existing shipping schedule is:

[0023]

[0024] in: It is a collection of ships with non-empty sailing schedules; is the number of non-empty ships on the sailing schedule; It is the available time of a non-empty vessel.

[0025] Preferably, the constraints of the ocean shipping ship scheduling model based on the existing ship schedule are as follows:

[0026] Ship collection: S, s i ∈S,i=1,...,n, i represents the number of a ship, s i represents the ship numbered i, and n represents the total number of n ships in the set S;

[0027] The set of ships with non-empty sailing schedules: in Representing a collection There are The vessel has no empty sailing schedule;

[0028] Ship standard speed set: V, v(s i )∈V,s i ∈S;

[0029] Ship cargo capacity collection: SC, sc(s i )∈SC,s i ∈S, sc(s i ) indicates ship s i cargo capacity;

[0030] Vessel lease term: T, Respectively represent the start and end time of the lease of vessel i;

[0031] Goods collection: D, d l ∈D,l=1,...,m, l represents a certain cargo number, d l represents the goods numbered l, and m represents the total number of goods in set D;

[0032] Cargo loading volume SZ, sz(d l )∈SZ,d l ∈D,sz(d l ) indicates goods d l Loading capacity;

[0033] Cargo loading time collection: tg(d l )∈TG, d l ∈D, t (d l )and Represents goods d l The loading start time and loading end time;

[0034] Cargo loading port collection: PO, po(d l )∈PO,d l ∈D,po(d l ) indicates goods d l loading port;

[0035] Cargo unloading port collection: PD, pd(d l )∈PD,d l ∈D,pd(d l ) indicates goods d l unloading port;

[0036] The port route distance is expressed as:

[0037] rt(po(d l ),pd(d l ))∈RT,po(d l )∈PO,pd(d l )∈PD

[0038] Among them, rt(po(d l ),pd(d l )) indicates port po(d l ) to port pd(d l ) between the two routes;

[0039] Ships iFrom the port po(d l ) to port pd(d l )’s flight time is expressed as:

[0040] Δt(po(d l ),pd(d l ),v(s i ))=rt(po(d l ),pd(d l )) / v(s i );

[0041] Ships i A collection of transport plans:

[0042] PL(s i )=(ST(s i ),SD(s i ))

[0043] Among them, ST(s i ) indicates ship s i The transport time window set, SD(s i ) indicates ship s i The transport cargo collection;

[0044]

[0045] Where j1=1,...,p(s i ), where j1 represents the ship s i The j1th transportation plan,

[0046] Among them, p(s i ) indicates ship s i ∈S has p(s i ) transport plans.

[0047] Preferably, the ocean transport vessel scheduling model based on the existing ship schedule is:

[0048] Ships i The time corresponding to the j1-th transportation plan is expressed as:

[0049]

[0050] in, Indicates ships i The start time of the j1th transportation plan,

[0051] in, Indicates ships i The end time of the j1th transportation plan;

[0052] Shipsi The cargo corresponding to the j1-th transportation plan is expressed as:

[0053] The minimum available time of a ship is: Tmin;

[0054] According to the ship i The transportation plan can be used to obtain the ship s i Available time window set OPT(s i ):

[0055]

[0056] Where j2 represents the ship s i The j2th available time window;

[0057] represents the start time of the j2th available time window; The end time of the j2th available time window;

[0058] Ships i Available time:

[0059]

[0060] Among them, the function

[0061] Solving the above ship scheduling model, we can get cargo d l The corresponding feasible solution set SCH(s i ,d l )for:

[0062]

[0063] in, t (s i )and Ships i For this cargo l The start and end time points of the transportation plan;

[0064] Goods l The corresponding optimal arrangement solution is defined as:

[0065]

[0066] in, t o (s i )and Ships i For this cargo lThe start and end time points of the optimal transportation plan.

[0067] As a preference, in step 2, a set of goods to be arranged DP is given, wherein and ships i ∈S,i=1,...,n, where Indicates the number of goods to be arranged.

[0068] As a preference, in step three, Ship collection and The initialization process is as follows:

[0069] For all s i ∈S,

[0070] For all s i ∈S,

[0071] Among them, ST(s i ) indicates ship s i The set of transport time windows.

[0072] As a preferred method, in step 4, the cargo dp with the longest loading and unloading route distance in the set DP is k The formula for program arrangement is as follows:

[0073]

[0074] As a preferred method, in step eight, determine the cargo dp k Whether the empty time and full load time of the ship are within the available time window of the ship, and calculate the arrangement scheme sch(s i ,dp k ) and the reduction in optimization time Δopt(s i ,dp k ) is as follows,

[0075] 1) For all ships i ∈SG(dp k ), IF t (dp k )≥ T (s i ),

[0076] and po(sd1(s i )),v(s i )), then it means that the ship s i Able to arrange goods dp k ;

[0077] Its arrangement scheme sch(s i ,dp k )for:

[0078]

[0079] Use this window to arrange goods dp k , ships i Reduction in optimization time Δopt(s i ,dp k )for:

[0080]

[0081] 2) For all ships i ∈SG(dp k )

[0082] and

[0083] This means that the ship i Able to arrange goods dp k ;

[0084] Arrangement scheme sch(s i ,dp k )for:

[0085]

[0086] Use this time window to arrange the goods dp k , ships i Reduction in optimization time Δopt(s i ,dp k )for

[0087]

[0088] 3) For all ships i ∈SG(dp k ) and j1=1,...,p(s i ),

[0089] and This means that the ship i Able to arrange goods dp k ;

[0090] Arrangement scheme sch(s i ,dp k )for

[0091]

[0092] Use this window to arrange goods dp k , ships i The total reduction in optimizable time Δopt(s i ,dp k )for

[0093]

[0094] 4) If one of the conditions is met, it means that the cargo can be arranged in the ship. If none of the above three conditions are met, it means that the ship is i The goods dp is not met k If the transport time window fails, the ship s i From cargo dp k Available ship collection SG(dp k ) in the elimination, namely SG(dp k )=SG(dp k )-s i .

[0095] As a preference, in step 13, if the set If it is not empty, then the set of ships with empty sailing schedules is required. To arrange the goods, the steps are as follows:

[0096] Step 14: Select a collection The ship with the smallest cargo capacity is added to the set as the available ship for the failed cargo set DF. and remove the ship with the smallest cargo capacity from the set Delete in;

[0097] Step 15: Add the goods in the failed arrangement goods set DF to the to-be-arranged goods set DP, delete all the goods in the DF set, and jump to step 4 for re-arrangement.

[0098] Compared with the existing technology, the advantages of the present invention are: for the scenario of ocean-going shipping of bulk industrial materials, the present invention constructs a multi-cargo fleet ship transportation scheduling optimization model. By setting ship screening and scheduling optimization rules, on the basis of ensuring the optimal overall available time of the fleet, the present invention gradually iteratively optimizes and finally arranges the generated cargo ship transportation plan based on the rules, reducing the complexity of problem solving and improving the efficiency of algorithm optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0099] Figure 1The flowchart of the method for scheduling ocean transport vessels based on rules of the present invention is shown.

[0100] Figure 2 This is a schematic diagram of the cargo and ship transportation plan to be arranged.

[0101] Figure 3 The result diagram of the arrangement of the ocean transport vessel scheduling method based on the rule of the present invention is shown. DETAILED DESCRIPTION

[0102] The present invention aims to solve the problem of arranging ocean-going shipping plans for bulk industrial materials. Based on the existing ship schedule, the present invention dynamically analyzes the ship utilization time and schedules and generates cargo transportation plans. The evaluation criteria for the quality of the scheduling results are as follows: (1) The available time of the fleet after scheduling is the longest, where the available time refers to the continuous idle time period of a ship that is not less than the required time Tmin. If the ship has available time, it means that the ship can be rented out to earn rent or can be used to optimize the arrangement of subsequent cargo within the available time. If the idle time period is too short, it means that there is a high probability that no cargo will be arranged in the idle time period. (2) The scheduling plan is arranged as much as possible to ships with existing schedules to maximize the utilization rate of existing ships.

[0103] The present invention will be further described below with reference to implementation cases:

[0104] 1. Establish an ocean shipping vessel scheduling model based on existing shipping schedules:

[0105] 1. The ocean shipping ship scheduling model designed based on the existing shipping schedule is as follows:

[0106] Objective function:

[0107] in: It is a collection of ships with non-empty sailing schedules; is the number of non-empty ships on the sailing schedule; It is the available time of a non-empty vessel.

[0108] Interpretation: The number of ships with scheduled tasks is the least, and the available time for scheduled tasks is the largest.

[0109] Constraints:

[0110] Ship collection: S, s i ∈S,i=1,...,n, i represents the number of a ship, s i represents the ship numbered i, and n represents the total number of n ships in the set S;

[0111] The set of ships with non-empty sailing schedules: in Representing a collection There are The vessel has no empty sailing schedule;

[0112] Ship standard speed set: V, v(s i )∈V,s i ∈S

[0113] Ship cargo capacity collection: SC, sc(s i )∈SC,s i ∈S, sc(s i ) indicates ship s i cargo capacity;

[0114] Vessel lease term: T, s i ∈S, T (s i ), Respectively represent the start and end time of the lease of vessel i;

[0115] Goods collection: D, d l ∈D,l=1,...,m, l represents a certain cargo number, d l represents the goods numbered l, and m represents the total number of goods in set D;

[0116] Cargo loading volume SZ, sz(d l )∈SZ,d l ∈D,sz(d l ) indicates goods d l Loading capacity;

[0117] Cargo loading time collection: tg(d l )∈TG, d l ∈D, t (d l )and Represents goods d l The loading start time and loading end time;

[0118] Cargo loading port collection: PO, po(d l )∈PO,d l ∈D,po(d l ) indicates goods d l loading port;

[0119] Cargo unloading port collection: PD, pd(d l )∈PD,d l ∈D,pd(d l ) indicates goods d l unloading port;

[0120] The port route distance is expressed as:

[0121] rt(po(d l ),pd(d l ))∈RT,po(d l )∈PO,pd(d l )∈PD

[0122] Among them, rt(po(d l ),pd(d l )) indicates port po(d l ) to port pd(d l ) between the two routes;

[0123] Ships i From the port po(d l ) to port pd(d l )’s flight time is expressed as:

[0124] Δt(po(d l ),pd(d l ),v(s i ))=rt(po(d l ),pd(d l )) / v(s i )

[0125] Ships i A collection of transport plans:

[0126] PL(s i )=(ST(s i ),SD(s i ))

[0127] Among them, ST(s i ) indicates ship s i The transport time window set, SD(s i ) indicates ship s i of transport cargo.

[0128]

[0129] Where j1=1,...,p(s i ), where j1 represents the ship s i The j1th transportation plan, where p(s i ) indicates ship s i ∈S has p(s i ) transport plans.

[0130] Then, ship s i The time corresponding to the j1th transportation plan is expressed as

[0131]

[0132] in Indicates ships i The start time of the j1th transportation plan, Indicates ships i The end time of the j1th transportation plan.

[0133] Ships i The cargo corresponding to the j1-th transportation plan is expressed as

[0134] The minimum available time of a ship is: Tmin;

[0135] According to the ship i The transportation plan can be used to obtain the ship s i Available time window set OPT(s i ):

[0136]

[0137] Where j2 represents the ship s i The j2th available time window;

[0138] represents the start time of the j2th available time window; The end time of the j2th available time window;

[0139] Ships i Available time:

[0140]

[0141] Among them, the function

[0142] Solving the above ship scheduling model, we can get cargo d l The corresponding feasible solution set SCH(s i ,d l )for:

[0143]

[0144] in, t (s i )and Ships i For this cargo l The start and end time of the transportation plan.

[0145] Goods l The corresponding optimal arrangement solution is defined as:

[0146]

[0147] in, t o (s i )and Ships i For this cargo l The start and end time points of the optimal transportation plan.

[0148] 2. Given a set of goods to be arranged DP, where and ships i ∈S,i=1,...,n, where Indicates the number of goods to be arranged.

[0149] As can be seen from the above, the present invention is based on the ocean shipping ship scheduling model of the existing shipping schedule: for the ocean shipping scenario of bulk industrial materials, a multi-cargo fleet ship transportation scheduling optimization model is constructed. Based on the existing shipping schedule of the own fleet, by dynamically analyzing the empty sailing time from the previous voyage to the current voyage, the full sailing time of the current voyage, and the impact of the cargo of the current voyage on the empty sailing time of the next voyage, the ship transportation plan is arranged, thereby making the scheduling optimization more accurate. In addition, by constructing an available time indicator, the available time of the ship is maximized, providing support for arranging the next cargo or leasing it within the available time of the ship, thereby improving the overall utilization rate of the fleet.

[0150] 2. Using the rule-based ocean shipping scheduling method designed by the present invention to solve the optimal arrangement solution The steps are as follows, see Figure 1 :

[0151] (1) Initialize the failed arrangement goods set DF to be an empty set, that is:

[0152] (2) Initialize goods Collection of available ships and

[0153] in, It consists of ships with non-empty transportation plans in the ship set S, It consists of ships with empty transportation plans in the ship set S.

[0154] For goods Ship collection and The initialization process is as follows:

[0155] For all s i ∈S,

[0156] For all s i ∈S,

[0157] Among them, ST(s i ) indicates ship s i The set of transport time windows;

[0158] (3) Calculate the route distances in the set of goods to be arranged DP, and first arrange the goods dp with the longest route distance in the set DP. k :

[0159]

[0160] (4) According to the ship's cargo capacity and cargo loading capacity, the ship's cargo capacity is less than the cargo dp k Loading volume of the ship from cargo dp k Available ship collection SG(dp k ), that is, for all s i ∈SG(dp k ),

[0161] IF sc(s i ) <sz(dp k ),SG(dp k )=SG(dp k )-s i ;

[0162] (5) dp the goods k Loading time window tg(dp k ) The ship with cargo transportation plan from cargo dp k Available ship collection SG(dp k ), that is, for all s i ∈SG(dp k ),

[0163] or

[0164] (6) Determine SG(dp k ) is empty. If SG(dp k ) is empty, indicating that the goods dp k No available ship, jump to step 10; if SG(dp k ) is not empty, jump to the next step 7.

[0165] (7) For all ships i ∈SG(dp k), calculate the cargo dp k Available layout schemes are calculated as follows:

[0166] 1) For all ships i ∈SG(dp k ),

[0167] IF t (dp k )≥ T (s i ),

[0168] and pd(dp k ),v(s i ))≤ st 1(s i )-Δt(pd(dp k ),po(sd1(s i )),v(s i )),

[0169] This means that the ship i Able to arrange goods dp k ;

[0170] Its arrangement scheme sch(s i ,dp k )for:

[0171]

[0172] Use this window to arrange goods dp k , ships i Reduction in optimization time Δopt(s i ,dp k )for:

[0173]

[0174] 2) For all ships i ∈SG(dp k )

[0175] and

[0176]

[0177] This means that the ship i Able to arrange goods dp k ;

[0178] Arrangement scheme sch(s i ,dp k )for

[0179]

[0180] Use this time window to arrange the goods dp k , ships i Reduction in optimization time Δopt(s i ,dp k )for

[0181]

[0182] 3) For all ships i ∈SG(dp k ) and j1=1,...,p(s i ),

[0183] and

[0184]

[0185] This means that the ship i Able to arrange goods dp k , arrangement scheme sch(s i ,dp k )for

[0186]

[0187] Use this window to arrange goods dp k , ships i The total reduction in optimizable time Δopt(s i ,dp k )for

[0188] 4) If one of the conditions is met, it means that the cargo can be arranged in the ship. If none of the above three conditions are met, it means that the ship is i The goods dp is not met k The transport time window of , the arrangement fails. Then the ship s i From cargo dp k Available ship collection SG(dp k ) in the elimination, namely SG(dp k )=SG(dp k )-s i .

[0189] (8) Determine SG(dp k ) is empty. If SG(dp k ) is empty, indicating that the goods dp k Arrangement fails, jump to step 10; if SG(dp k) is not empty, jump to the next step 9.

[0190] (9) Solve minΔopt(s i ,dp k ), s i ∈SG(dp k ) corresponding ships s k , as cargo dp k The optimal arrangement scheme sch o (s k ,dp k ). dp the goods k The arrangement scheme sch o (s k ,dp k ) Update to ships k Sailing Schedule dp the goods k Add to the arranged goods collection D, and at the same time transfer the goods dp k Delete from the set to be arranged DP, that is: DP = DP-dp k , and skip to step 11.

[0191] (10) dp k Add to the arrangement failure set DF, that is: DF = DF∪dp k ; Change dp k Delete from the set to be arranged DP, that is: DP = DP-dp k , skip to the next step 11.

[0192] (11) Determine whether the set to be arranged DP is empty. If the set DP is not empty, jump to step 3 to arrange the next item. If the set DP is empty, it means there is no item to be arranged, jump to the next step 12.

[0193] (12) If the set DF is empty, return "all cargoes are arranged successfully" and output the updated ship schedule. If DF is not empty, it is necessary to determine the set of ships with empty schedules. Is it empty? If the collection If it is empty, it means that the cargo in the set DF cannot be arranged in all available ships, and the system returns "Cargo arrangement in set DF failed" and outputs the ship schedule of the cargo that is successfully arranged; if the set If it is not empty, then the set of ships with empty sailing schedules is required. Arrange the goods in the middle and skip to the next step 13.

[0194] (13) Select a set The ship with the smallest cargo capacity, namely min sz(s i ), As an available ship for the failed cargo collection DF, add it to the collection and remove the ship with the smallest cargo capacity from the set Delete in.

[0195] (14) Add the goods in the failed arrangement goods set DF back to the set of goods to be arranged DP, and delete all the goods in the DF set, that is: Skip to step 3 to rearrange.

[0196] In summary, the present invention proposes a rule-based ocean shipping vessel scheduling method for a constructed nonlinear ship scheduling optimization problem, comprehensively considering the complexity of the problem solution and the optimal solution. Based on the analysis of a large amount of prior data, scheduling rules such as prioritizing the scheduling of cargoes with long sailing times and prioritizing the use of ships with already scheduled cargoes are set. Ship screening and solution optimization are performed based on these various rules. This significantly reduces the number of iterative optimization iterations while ensuring the available time for the scheduling solution, thereby improving the success rate of the solution scheduling and the utilization rate of ships. For the optimization problem of M cargoes and N ships, the maximum number of algorithm iterative optimization iterations is M×N. While ensuring the available time, the number of iterative optimization iterations is increased to improve the success rate of the scheduling and the utilization rate of ships.

[0197] The examples are as follows:

[0198] S1: Assume that there are 3 ships in the fleet, numbered as ship 1, ship 2, and ship 3. Their transportation plan is as follows: Figure 2 As shown, a transportation plan for cargo 6 needs to be formulated, wherein the loading information of cargo 6 is shown in the following table.

[0199] Table 1 Details of Goods 6

[0200] type Details Loading start time July 12 Loading end time July 13 loading port Port of Savannah (USA) Unloading port Fangchenggang (China) Route distance 14,000 nautical miles Average speed 16 sections Sailing time 36 days Loading capacity 80,000 tons

[0201] S2: After adopting the ocean transport ship scheduling method of the present invention, Figure 3It can be seen that Ship 1, Ship 2, and Ship 3 all have transportation time windows that meet the requirements for the cargo. Using the rule-based ocean shipping ship scheduling method of the present invention, based on the optimization objectives of minimizing the number of non-empty ships on a scheduled sailing date and maximizing the available time of non-empty ships on a scheduled sailing date, the optimal transportation plan for cargo 6 can be solved for Ship 1, with the transportation plan being [June 15, July 29], where [June 15, July 12] is the sailing time from the previous unloading port of cargo 6 to the loading port of the current voyage, and [July 13, July 29] is the sailing time from the loading port to the unloading port of the current voyage.

[0202] The above is a detailed introduction to a rule-based ocean transport ship scheduling method provided by the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core ideas. At the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scopes. Changes and improvements to the present invention will be possible without exceeding the concept and scope specified in the appended claims. In summary, the contents of this specification should not be understood as limiting the present invention.

Claims

1. A rule-based ocean shipping vessel scheduling method, characterized by: The steps are as follows: Step 1: Establish an ocean shipping vessel scheduling model based on the existing shipping schedule; Step 2: Given the set of goods to be arranged DP, initialize the set of goods that failed to be arranged DF; Step 3: Initialize the set of available ships for cargo and described It consists of ships with non-empty transportation plans in the ship set S, It consists of ships with empty transport plans in the ship set S; Step 4: Calculate the route distances in the cargo set DP to be arranged, and select the cargo dp with the longest loading and unloading route distance in the set DP k Arrange plans; Step 5: Set the ship's cargo capacity to be less than the cargo dp k Loading volume of the ship, from cargo dp k Available ship collection SG(dp k ) Step 6: dp the goods k Loading time window tg(dp k ) has cargo transportation plan, from cargo dp k Available ship collection SG(dp k ) Step 7: Determine the available ship set SG(dp k ) is empty, if SG(dp k ) is empty, indicating that the goods dp k No available ship, jump to step 11; if SG(dp k ) is not empty, jump to the next step; Step 8: According to the goods dp k Loading time window tg(dp k ), loading and unloading routes, existing transportation plans for ships, and for all ships i ∈SG(dp k ), determine the cargo dp k Whether the empty time and full load time of the ship are within the available time window of the ship, for cargo dp k The ship of the transport time window is calculated as the arrangement scheme sch(s i ,dp k ) and the reduction in optimization time Δopt(s i ,dp k ), for no goods dp k The ship of the transportation time window is selected from the available ship set SG(dp k ) Step 9: Determine the available ship set SG(dp k ) is empty, if the available ship set SG(dp k ) is empty, indicating that the goods dp k Arrangement fails, jump to step 11; if the available ship set SG (dp k ) is not empty, jump to the next step; Step 10, solve minΔopt(s i ,dp k ), s i ∈SG(dp k ) corresponding ships s k , as cargo dp k The optimal arrangement scheme sch o (s k ,dp k ), dp the goods k The arrangement scheme sch o (s k ,dp k ) Update to ships k Sailing Schedule dp the goods k Add to the arranged goods collection D, and at the same time transfer the goods dp k Delete from the set to be arranged DP, that is: DP = DP-dp k , and jump to step 12; Step 11: dp the goods k Add it to the arrangement failure set DF, delete it from the set to be arranged DP, and jump to the next step; Step 12: Determine whether the set to be arranged DP is empty. If the set to be arranged DP is not empty, jump to step 4 to arrange the next item. If the failed arrangement set DP is empty, it means there is no goods to be arranged, and jump to the next step; Step 13: Determine whether the failed arrangement set DF is empty. If the failed arrangement set DF is empty, it means that all cargoes have been arranged successfully, and the updated ship schedule is output; If the arrangement failure set DF is not empty, it is necessary to determine the set of ships whose sailing schedules are empty. Is it empty? If the collection If it is empty, it means that the goods in the set DF cannot be arranged in all available ships, which means that the arrangement of the goods in the set DF has failed, and the ship schedule of the successfully arranged goods is output.

2. The rule-based ocean shipping ship scheduling method according to claim 1, characterized in that: In step 1, the objective function of the ocean shipping ship scheduling model based on the existing ship schedule is in: It is a collection of ships with non-empty sailing schedules; is the number of non-empty ships on the sailing schedule; It is the available time of a non-empty vessel.

3. A rule-based ocean shipping ship scheduling method according to claim 2, characterized in that: The constraints of the ocean shipping ship scheduling model based on the existing ship schedule are as follows: Ship collection: S, s i ∈S,i=1,...,n, i represents the number of a ship, s i represents the ship numbered i, and n represents the total number of n ships in the set S; The set of ships with non-empty sailing schedules: in Representing a collection There are The vessel has no empty sailing schedule; Ship standard speed set: V, v(s i )∈V,s i ∈S; Ship cargo capacity collection: SC, sc(s i )∈SC,s i ∈S, sc(s i ) indicates ship s i cargo capacity; Vessel lease term: T, Respectively represent the start and end time of the lease of vessel i; Goods collection: D, d l ∈D,l=1,...,m, l represents a certain cargo number, d l represents the goods numbered l, and m represents the total number of goods in set D; Cargo loading volume SZ, sz(d l )∈SZ,d l ∈D,sz(d l ) indicates goods d l Loading capacity; Cargo loading time collection: and Represents goods d l The loading start time and loading end time; Cargo loading port collection: PO, po(d l )∈PO,d l ∈D,po(d l ) indicates goods d l loading port; Cargo unloading port collection: PD, pd(d l )∈PD,d l ∈D,pd(d l ) indicates goods d l unloading port; The port route distance is expressed as: rt(po(d l ),pd(d l ))∈RT,po(d l )∈PO,pd(d l )∈PD Among them, rt(po(d l ),pd(d l )) indicates port po(d l ) to port pd(d l ) between the two routes; Ships i From the port po(d l ) to port pd(d l )’s flight time is expressed as: Δt(po(d l ),pd(d l ),v(s i ))=rt(po(d l ),pd(d l )) / v(s i ); Ships i A collection of transport plans: PL(s i )=(ST(s i ),SD(s i )) Among them, ST(s i ) indicates ship s i The transport time window set, SD(s i ) indicates ship s i The transport cargo collection; Where j1=1,...,p(s i ), where j1 represents the ship s i The j1th transportation plan, Among them, p(s i ) indicates ship s i ∈S has p(s i ) transport plans.

4. The rule-based ocean shipping ship scheduling method according to claim 3, characterized in that: The ocean shipping ship scheduling model based on the existing ship schedule, Ships i The time corresponding to the j1-th transportation plan is expressed as: in, Indicates ships i The start time of the j1th transportation plan, in, Indicates ships i The end time of the j1th transportation plan; Ships i The cargo corresponding to the j1th transportation plan is expressed as: sd j1 (s i )∈D; The minimum available time of a ship is: Tmin; According to the ship i The transportation plan can be used to obtain the ship s i Available time window set OPT(s i ): Where j2 represents the ship s i The j2th available time window; represents the start time of the j2th available time window; The end time of the j2th available time window; Ships i Available time: Among them, the function Solving the above ship scheduling model, we can get cargo d l The corresponding feasible solution set SCH(s i ,d l )for: in, t (s i )and Ships i For this cargo l The start and end time points of the transportation plan; Goods l The corresponding optimal arrangement solution is defined as: in, t o (s i )and Ships i For this cargo l The start and end time points of the optimal transportation plan.

5. The rule-based ocean shipping vessel scheduling method according to claim 1, characterized in that: In step 2, a set of goods to be arranged DP is given, where and ships i ∈S,i=1,...,n, where Indicates the number of goods to be arranged.

6. The rule-based ocean shipping ship scheduling method according to claim 1, characterized in that: In step three, the goods Ship collection and The initialization process is as follows: For all s i ∈S, For all s i ∈S, Among them, ST(s i ) indicates ship s i The set of transport time windows.

7. The rule-based ocean shipping vessel scheduling method according to claim 1, characterized in that: In step 4, the cargo dp with the longest loading and unloading route distance in the set DP is k The formula for program arrangement is as follows:

8. The rule-based ocean shipping vessel scheduling method according to claim 4, characterized in that: In step eight, determine the cargo dp k Whether the empty time and full load time of the ship are within the available time window of the ship, and calculate the arrangement scheme sch(s i ,dp k ) and the reduction in optimization time Δopt(s i ,dp k ) is as follows, 1) For all ships i ∈SG(dp k ), IF t (dp k )≥ T (s i ), and This means that the ship i Able to arrange goods dp k ; Its arrangement scheme sch(s i ,dp k )for: Use this window to arrange goods dp k , ships i Reduction in optimization time Δopt(s i ,dp k )for: 2) For all ships i ∈SG(dp k ) and This means that the ship i Able to arrange goods dp k ; Arrangement scheme sch(s i ,dp k )for Use this time window to arrange the goods dp k , ships i Reduction in optimization time Δopt(s i ,dp k )for 3) For all ships i ∈SG(dp k ) and j1=1,...,p(s i ), and This means that the ship i Able to arrange goods dp k ; Arrangement scheme sch(s i ,dp k )for: Use this window to arrange goods dp k , ships i The total reduction in optimizable time Δopt(s i ,dp k )for 4) If one of the conditions is met, it means that the cargo can be arranged in the ship. If none of the above three conditions are met, it means that the ship is i The goods dp is not met k If the transport time window fails, the ship s i From cargo dp k Available ship collection SG(dp k ) in the elimination, namely SG(dp k )=SG(dp k )-s i .

9. The rule-based ocean shipping vessel scheduling method according to claim 1, characterized in that: In step 13, if the set If it is not empty, then the set of ships with empty sailing schedules is required. To arrange the goods, the steps are as follows: Step 14: Select a collection The ship with the smallest cargo capacity is added to the set as the available ship for the failed cargo set DF. and remove the ship with the smallest cargo capacity from the set Delete in; Step 15: Add the goods in the failed arrangement goods set DF to the to-be-arranged goods set DP, delete all the goods in the DF set, and jump to step 4 for re-arrangement.

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